Spark Job Management

Based on the open-source Spark, DLI optimizes performance and reconstructs services to be compatible with the Apache Spark ecosystem and interfaces, and executes batch processing tasks.

DLI also allows you to use Spark jobs to access DLI metadata.

Spark job management provides the following functions:

Creating a Spark Job
Re-executing a Job
Searching for a Job
Terminating a Job

In addition, you can click Quick Links to switch to the details on User Guide.

Spark Jobs Page

On the Overview page, click Spark Jobs to go to the SQL job management page. Alternatively, you can click Job Management > Spark Jobs. The page displays all Spark jobs. If there are a large number of jobs, they will be displayed on multiple pages. DLI allows you to view jobs in all statuses.

**Table 1** Job management parameters
Parameter	Description
Job ID	ID of a submitted Spark job, which is generated by the system by default.
Name	Name of a submitted Spark job.
Queues	Queue where the submitted Spark job runs
Username	Name of the user who executed the Spark job
Status	Job status. The following values are available: Starting: The job is being started. Running: The job is being executed. Failed: The session has exited. Finished: The session is successfully executed. Restoring: The job is being restored.
Created	Time when a job is created. Jobs can be displayed in ascending or descending order of the job creation time.
Last Modified	Time when a job is completed.
Operation	Edit: You can modify the current job configuration and re-execute the job. SparkUI: After you click this button, the Spark job execution page is displayed. NOTE: The SparkUI page cannot be viewed for jobs in the Starting state. Currently, only the latest 100 job information records are displayed on the SparkUI of DLI. Terminate Job: Cancel a job that is being started or running. Re-execute: Run the job again. Archive Log: Save job logs to the temporary bucket created by DLI. Commit Log: View the logs of submitted jobs. Driver Log: View the logs of running jobs.

Re-executing a Job

On the Spark Jobs page, click Edit in the Operation column of the job. On the Spark job creation page that is displayed, modify parameters as required and execute the job.